Self-learning spatial recognition system

ABSTRACT

A method includes receiving a plurality of video frames from a video source, wherein each video frame of the plurality of video frames comprises a view of a geolocation. The method further includes detecting a first object entering a first side of a first video frame of the plurality of video frames. The method further includes determining, from the plurality of video frames, that the first object has stopped in an area of the geolocation for at least a threshold amount of time. The method further includes detecting the first object leaving a second side of a second video frame of the plurality of video frames. The method further includes identifying, by a computer processing device, the area of the geolocation as a region of interest based on the detecting the first object leaving.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication No. 62/520,328, filed Jun. 15, 2017, the entire contents ofwhich are hereby incorporated by reference.

BACKGROUND

This disclosure relates to a self-learning spatial recognition systemand, more particularly, to a self-learning spatial recognition system ina publish-subscribe (or “PubSub”) system.

The PubSub pattern is a data communication messaging arrangementimplemented by software systems where so-called publishers publishmessages to topics and so-called subscribers receive the messagespertaining to particular topics to which they are subscribed. There canbe one or more publishers per topic and publishers generally have noknowledge of what subscribers, if any, will receive the publishedmessages. Because publishers may publish large volumes of messages andsubscribers may subscribe to many topics (or “channels”), the overallvolume of messages directed to a particular channel and/or subscribermay be difficult to manage.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates an example system that supports the PubSubcommunication pattern.

FIG. 1B illustrates functional layers of software on an example clientdevice.

FIG. 2 is a diagram of an example messaging system.

FIG. 3A is a data flow diagram of an example method for writing data toa streamlet.

FIG. 3B is a data flow diagram of an example method for reading datafrom a streamlet.

FIG. 4A is a data flow diagram of an example method for publishingmessages to a channel of a messaging system.

FIG. 4B is a data flow diagram of an example method for subscribing to achannel of a messaging system.

FIG. 4C is an example data structure for storing messages of a channelof a messaging system.

FIG. 5A is a data flow diagram of an example method for publishing andreplicating messages of a messaging system.

FIG. 5B is a data flow diagram of an example method for retrievingstored messages in a messaging system.

FIGS. 5C and 5D are data flow diagrams of example methods for repairinga chain of copies of data in a messaging system.

FIG. 6 is an example data flow diagram for the application of filteringcriteria in a messaging system.

FIGS. 7A-7D are illustrations of how messages may be processed usingquery instructions that include a period-based parameter.

FIG. 8 is a diagram of an example messaging system for self-learningspatial recognition in a PubSub communication system.

FIG. 9 is a first flowchart of an example method for self-learningspatial recognition in a PubSub communication system.

FIG. 10 is a second flowchart of an example method for self-learningspatial recognition in a PubSub communication system.

FIG. 11 is a third flowchart of an example method for self-learningspatial recognition in a PubSub communication system.

FIG. 12 is a diagram of an example mapping for self-learning spatialrecognition in a PubSub communication system.

FIG. 13 is a block diagram of an example computing device that mayperform one or more of the operations described herein.

DETAILED DESCRIPTION

Elements of examples or embodiments described with respect to a givenaspect of the invention can be used in various embodiments of anotheraspect of the invention. For example, it is contemplated that featuresof dependent claims depending from one independent claim can be used inapparatus, systems, and/or methods of any of the other independentclaims.

The details of one or more embodiments of the subject matter describedin this specification are set forth in the accompanying drawings and thedescription below. Other features, aspects, and advantages of thesubject matter will become apparent from the description, the drawings,and the claims.

System architecture for self-learning spatial recognition may include amessaging system. The messaging system may support the PubSubcommunication pattern and may allow publishers and subscribers topublish and receive live messages. Users may include both publishers andsubscribers in the messaging system. For example, publishers may publishmessages via the messaging system that indicate useful information tosubscribers. The subscribers may view the messages and associatedinformation. It is noted the present embodiments may also be implementedusing other suitable (non-PubSub) real-time or near real-time networktopologies.

In certain embodiments, systems may track free or open geographicalareas (e.g., parking lot spots) with a webcam or other suitable video orcamera source if a map of the geographical area (e.g., parking lot) isavailable. For example, if a map of a parking lot already exists,defined parking spots may be labeled via either human intervention orcomputer-based artificial intelligence. However, if the parking lot islarge and there are no markers or other identifiers on the parking lotsurface (or the marks are not obvious or easily seen), detecting free oropen parking spots in the parking lot may be problematic. Even ifpossible using existing methods, such methods of detecting free or openparking spots may be time-consuming, resource, and processor intensive.Accordingly, it would be desirable to provide systems and methods forself-learning spatial recognition, where current approaches cannotprovide such spatial recognition without human intervention, and whileminimizing computer resources and processing power.

Advantageously, the systems and methods of self-learning spatialrecognition described herein resolve the above problems, and others, byutilizing a PubSub computing network to identify regions of interest(e.g., parking spots, seats, boat slips, spots in a queue, etc.) in ageographical location (e.g., parking lots, parking structures, streets,harbors, restaurants, sports complexes, theatres, parks, open fields,shopping areas, etc.). The present embodiments may provide techniquesfor resource and processing power minimizing self-learning spatialrecognition, and may thereby increase processing capability and/orcapacity and data throughput within the PubSub computing network.

Worth noting is that while the term “vehicle” is used throughout forconvenience and simplicity, the term “vehicle” may refer to one of, forexample, a bike, a skateboard, an automotive motor vehicle, amotorcycle, a scooter, a boat, an airplane, a train, a jet, or othersuitable conveyance. Furthermore, the term “pedestrian” as usedthroughout may include both humans and animals.

FIG. 1A illustrates an example system 100 that supports the PubSubcommunication pattern. The example system 100 may support videostreaming by providing messages from publishers to subscribers thatinclude a video frame, for instance. Components of the example system100 may also provide support for querying and updating live videostreams. Publisher clients (e.g., Publisher 1) can publish messages tonamed channels (e.g., “Channel 1”) by way of the system 100. A messagecan comprise any type of information including one or more of thefollowing: text, image content, sound content, multimedia content, videocontent, binary data, and so on. Other types of message data arepossible. Subscriber clients (e.g., Subscriber 2) can subscribe to anamed channel using the system 100 and start receiving messages whichoccur after the subscription request or from a given position (e.g., amessage number or time offset). A client can be both a publisher and asubscriber.

Depending on the configuration, a PubSub system can be categorized asfollows:

-   -   One to One (1:1). In this configuration there is one publisher        and one subscriber per channel. A typical use case is private        messaging.    -   One to Many (1:N). In this configuration there is one publisher        and multiple subscribers per channel. Typical use cases are        broadcasting messages (e.g., stock prices).    -   Many to Many (M:N). In this configuration there are many        publishers publishing to a single channel. The messages are then        delivered to multiple subscribers. Typical use cases are map        applications.

There is no separate operation needed to create a named channel. Achannel is created implicitly when the channel is subscribed to or whena message is published to the channel. In some implementations, channelnames can be qualified by a name space. A name space comprises one ormore channel names. Different name spaces can have the same channelnames without causing ambiguity. The name space name can be a prefix ofa channel name where the name space and channel name are separated by adot or other suitable separator. In some implementations, name spacescan be used when specifying channel authorization settings. Forinstance, the messaging system 100 may have app1.foo andapp1.system.notifications channels where “app1” is the name of the namespace. The system can allow clients to subscribe and publish to theapp1.foo channel. However, clients can only subscribe to, but notpublish to the app1.system.notifications channel.

FIG. 1B illustrates functional layers of software on an example clientdevice. A client device (e.g., client 102) is a data processingapparatus such as, for example, a personal computer, a laptop computer,a tablet computer, a smart phone, a smart watch, or a server computer.Other types of client devices are possible. The application layer 104comprises the end-user application(s) that will integrate with thePubSub system 100. The messaging layer 106 is a programmatic interfacefor the application layer 104 to utilize services of the system 100 suchas channel subscription, message publication, message retrieval, userauthentication, and user authorization. In some implementations, themessages passed to and from the messaging layer 106 are encoded asJavaScript Object Notation (JSON) objects. Other message encodingschemes are possible.

The operating system 108 layer comprises the operating system softwareon the client 102. In various implementations, messages can be sent andreceived to/from the system 100 using persistent or non-persistentconnections. Persistent connections can be created using, for example,network sockets. A transport protocol such as TCP/IP layer 112implements the Transport Control Protocol/Internet Protocolcommunication with the system 100 that can be used by the messaginglayer 106 to send messages over connections to the system 100. Othercommunication protocols are possible including, for example, UserDatagram Protocol (UDP). In further implementations, an optionalTransport Layer Security (TLS) layer 110 can be employed to ensure theconfidentiality of the messages.

FIG. 2 is a diagram of an example messaging system 100. The system 100provides functionality for implementing PubSub communication patterns.The system comprises software components and storage that can bedeployed at one or more data centers 122 in one or more geographiclocations, for example. The system comprises MX nodes (e.g., MX nodes ormultiplexer nodes 202, 204 and 206), Q nodes (e.g., Q nodes or queuenodes 208, 210 and 212), one or more configuration manager nodes (e.g.,configuration manager 214), and optionally one or more C nodes (e.g., Cnodes or cache nodes 220 and 222). Each node can execute in a virtualmachine or on a physical machine (e.g., a data processing apparatus).Each MX node can serve as a termination point for one or more publisherand/or subscriber connections through the external network 216. Theinternal communication among MX nodes, Q nodes, C nodes, and theconfiguration manager can be conducted over an internal network 218, forexample. By way of illustration, MX node 204 can be the terminus of asubscriber connection from client 102. Each Q node buffers channel datafor consumption by the MX nodes. An ordered sequence of messagespublished to a channel is a logical channel stream. For example, ifthree clients publish messages to a given channel, the combined messagespublished by the clients comprise a channel stream. Messages can beordered in a channel stream, for example, by time of publication by theclient, by time of receipt by an MX node, or by time of receipt by a Qnode. Other ways for ordering messages in a channel stream are possible.In the case where more than one message would be assigned to the sameposition in the order, one of the messages can be chosen (e.g.,randomly) to have a later sequence in the order. Each configurationmanager node is responsible for managing Q node load, for example, byassigning channels to Q nodes and/or splitting channel streams intoso-called streamlets. Streamlets are discussed further below. Theoptional C nodes provide caching and load removal from the Q nodes.

In the example messaging system 100, one or more client devices(publishers and/or subscribers) establish respective persistentconnections (e.g., TCP connections) to an MX node (e.g., MX node 204).The MX node serves as a termination point for these connections. Forinstance, external messages (e.g., between respective client devices andthe MX node) carried by these connections can be encoded based on anexternal protocol (e.g., JSON). The MX node terminates the externalprotocol and translates the external messages to internal communication,and vice versa. The MX nodes publish and subscribe to streamlets onbehalf of clients. In this way, an MX node can multiplex and mergerequests of client devices subscribing for or publishing to the samechannel, thus representing multiple client devices as one, instead ofone by one.

In the example messaging system 100, a Q node (e.g., Q node 208) canstore one or more streamlets of one or more channel streams. A streamletis a data buffer for a portion of a channel stream. A streamlet willclose to writing when its storage is full. A streamlet will close toreading and writing and be de-allocated when its time-to-live (TTL) hasexpired. By way of illustration, a streamlet can have a maximum size of1 MB and a TTL of three minutes. Different channels can have streamletslimited by different sizes and/or by different TTLs. For instance,streamlets in one channel can exist for up to three minutes, whilestreamlets in another channel can exist for up to 10 minutes. In variousimplementations, a streamlet corresponds to a computing process runningon a Q node. The computing process can be terminated after thestreamlet's TTL has expired, thus freeing up computing resources (forthe streamlet) back to the Q node, for example.

When receiving a publish request from a client device, an MX node (e.g.,MX node 204) makes a request to a configuration manager (e.g.,configuration manager 214) to grant access to a streamlet to write themessage being published. Note, however, that if the MX node has alreadybeen granted write access to a streamlet for the channel (and thechannel has not been closed to writing), the MX node can write themessage to that streamlet without having to request a grant to accessthe streamlet. Once a message is written to a streamlet for a channel,the message can be read by MX nodes and provided to subscribers of thatchannel.

Similarly, when receiving a channel subscription request from a clientdevice, an MX node makes a request to a configuration manager to grantaccess to a streamlet for the channel from which messages are read. Ifthe MX node has already been granted read access to a streamlet for thechannel (and the channel's TTL has not been closed to reading), the MXnode can read messages from the streamlet without having to request agrant to access the streamlet. The read messages can then be forwardedto client devices that have subscribed to the channel. In variousimplementations, messages read from streamlets are cached by MX nodes sothat MX nodes can reduce the number of times needed to read from thestreamlets.

By way of illustration, an MX node can request a grant from theconfiguration manager that allows the MX node to store a block of datainto a streamlet on a particular Q node that stores streamlets of theparticular channel. Example streamlet grant request and grant datastructures are as follows:

StreamletGrantRequest={

-   -   “channel”: string( )    -   “mode”: “read”|“write”    -   “position”: 0

}

StreamletGrantResponse={

-   -   “streamlet-id”: “abcdef82734987”,    -   “limit-size”: 2000000, #2 megabytes max    -   “limit-msgs”: 5000, #5 thousand messages max    -   “limit-life”: 4000, # the grant is valid for 4 seconds    -   “q-node”: string( )    -   “position”: 0

}

The StreamletGrantRequest data structure stores the name of the streamchannel and a mode indicating whether the MX node intends on readingfrom or writing to the streamlet. The MX node sends theStreamletGrantRequest to a configuration manager node. The configurationmanager node, in response, sends the MX node a StreamletGrantResponsedata structure. The StreamletGrantResponse contains an identifier of thestreamlet (streamlet-id), the maximum size of the streamlet(limit-size), the maximum number of messages that the streamlet canstore (limit-msgs), the TTL (limit-life), and an identifier of a Q node(q-node) on which the streamlet resides. The StreamletGrantRequest andStreamletGrantResponse can also have a position field that points to aposition in a streamlet (or a position in a channel) for reading fromthe streamlet.

A grant becomes invalid once the streamlet has closed. For example, astreamlet is closed to reading and writing once the streamlet's TTL hasexpired and a streamlet is closed to writing when the streamlet'sstorage is full. When a grant becomes invalid, the MX node can request anew grant from the configuration manager to read from or write to astreamlet. The new grant will reference a different streamlet and willrefer to the same or a different Q node depending on where the newstreamlet resides.

FIG. 3A is a data flow diagram of an example method for writing data toa streamlet in various embodiments. In FIG. 3A, when an MX node (e.g.,MX node 202) request to write to a streamlet is granted by aconfiguration manager (e.g., configuration manager 214), as describedbefore, the MX node establishes a Transmission Control Protocol (TCP)connection with the Q node (e.g., Q node 208) identified in the grantresponse received from the configuration manager (302). A streamlet canbe written concurrently by multiple write grants (e.g., for messagespublished by multiple publisher clients). Other types of connectionprotocols between the MX node and the Q node are possible.

The MX node then sends a prepare-publish message with an identifier of astreamlet that the MX node wants to write to the Q node (304). Thestreamlet identifier and Q node identifier can be provided by theconfiguration manager in the write grant as described earlier. The Qnode hands over the message to a handler process 301 (e.g., a computingprocess running on the Q node) for the identified streamlet (306). Thehandler process can send to the MX node an acknowledgement (308). Afterreceiving the acknowledgement, the MX node starts writing (publishing)messages (e.g., 310, 312, 314, and 318) to the handler process, which inturn stores the received data in the identified streamlet. The handlerprocess can also send acknowledgements (316, 320) to the MX node for thereceived data. In some implementations, acknowledgements can bepiggy-backed or cumulative. For instance, the handler process can sendto the MX node an acknowledgement for every predetermined amount of datareceived (e.g., for every 100 messages received) or for everypredetermined time period (e.g., for every one millisecond). Otheracknowledgement scheduling algorithms, such as Nagle's algorithm, can beused.

If the streamlet can no longer accept published data (e.g., when thestreamlet is full), the handler process sends a Negative-Acknowledgement(NAK) message (330) indicating a problem, following by an EOF(end-of-file) message (332). In this way, the handler process closes theassociation with the MX node for the publish grant. The MX node can thenrequest a write grant for another streamlet from a configuration managerif the MX node has additional messages to store.

FIG. 3B is a data flow diagram of an example method for reading datafrom a streamlet in various embodiments. In FIG. 3B, an MX node (e.g.,MX node 204) sends to a configuration manager (e.g., configurationmanager 214) a request for reading a particular channel starting from aparticular message or time offset in the channel. The configurationmanager returns to the MX node a read grant including an identifier of astreamlet containing the particular message, a position in the streamletcorresponding to the particular message, and an identifier of a Q node(e.g., Q node 208) containing the particular streamlet. The MX node thenestablishes a TCP connection with the Q node (352). Other types ofconnection protocols between the MX node and the Q node are possible.

The MX node then sends to the Q node a subscribe message (354) with theidentifier of the streamlet (in the Q node) and the position in thestreamlet from which the MX node wants to read (356). The Q node handsover the subscribe message to a handler process 351 for the streamlet(356). The handler process can send to the MX node an acknowledgement(358). The handler process then sends messages (360, 364, 366), startingat the position in the streamlet, to the MX node. In someimplementations, the handler process can send all of the messages in thestreamlet to the MX node. After sending the last message in a particularstreamlet, the handler process can send a notification of the lastmessage to the MX node. The MX node can send to the configurationmanager another request for another streamlet containing a next messagein the particular channel.

If the particular streamlet is closed (e.g., after its TTL has expired),the handler process can send an unsubscribe message (390), followed byan EOF message (392), to close the association with the MX node for theread grant. The MX node can close the association with the handlerprocess when the MX node moves to another streamlet for messages in theparticular channel (e.g., as instructed by the configuration manager).The MX node can also close the association with the handler process ifthe MX node receives an unsubscribe message from a corresponding clientdevice.

In various implementations, a streamlet can be written into and readfrom at the same time instance. For example, there can be a valid readgrant and a valid write grant at the same time instance. In variousimplementations, a streamlet can be read concurrently by multiple readgrants (e.g., for channels subscribed to by multiple publisher clients).The handler process of the streamlet can order messages from concurrentwrite grants based on, for example, time-of-arrival, and store themessages based on the order. In this way, messages published to achannel from multiple publisher clients can be serialized and stored ina streamlet of the channel.

In the messaging system 100, one or more C nodes (e.g., C node 220) canoffload data transfers from one or more Q nodes. For instance, if thereare many MX nodes requesting streamlets from Q nodes for a particularchannel, the streamlets can be offloaded and cached in one or more Cnodes. The MX nodes (e.g., as instructed by read grants from aconfiguration manager) can read the streamlets from the C nodes instead.

As described above, messages for a channel in the messaging system 100are ordered in a channel stream. A configuration manager (e.g.,configuration manager 214) splits the channel stream into fixed-sizedstreamlets that each reside on a respective Q node. In this way, storinga channel stream can be shared among many Q nodes; each Q node stores aportion (one or more streamlets) of the channel stream. Moreparticularly, a streamlet can be stored in, for example, registersand/or dynamic memory elements associated with a computing process on aQ node, thus avoiding the need to access persistent, slower storagedevices such as hard disks. This results in faster message access. Theconfiguration manager can also balance load among Q nodes in themessaging system 100 by monitoring respective workloads of the Q nodesand allocating streamlets in a way that avoids overloading any one Qnode.

In various implementations, a configuration manager maintains a listidentifying each active streamlet, the respective Q node on which thestreamlet resides, an identification of the position of the firstmessage in the streamlet, and whether the streamlet is closed forwriting. In some implementations, Q nodes notify the configurationmanager and/or any MX nodes that are publishing to a streamlet that thestreamlet is closed due to being full or when the streamlet's TTL hasexpired. When a streamlet is closed, the streamlet remains on theconfiguration manager's list of active streamlets until the streamlet'sTTL has expired so that MX nodes can continue to retrieve messages fromthe streamlet.

When an MX node requests a write grant for a given channel and there isnot a streamlet for the channel that can be written to, theconfiguration manager allocates a new streamlet on one of the Q nodesand returns the identity of the streamlet and the Q node in theStreamletGrantResponse. Otherwise, the configuration manager returns theidentity of the currently open for writing streamlet and corresponding Qnode in the StreamletGrantResponse. MX nodes can publish messages to thestreamlet until the streamlet is full or the streamlet's TTL hasexpired, after which a new streamlet can be allocated by theconfiguration manager.

When an MX node requests a read grant for a given channel and there isnot a streamlet for the channel that can be read from, the configurationmanager allocates a new streamlet on one of the Q nodes and returns theidentity of the streamlet and the Q node in the StreamletGrantResponse.Otherwise, the configuration manager returns the identity of thestreamlet and Q node that contains the position from which the MX nodewishes to read. The Q node can then begin sending messages to the MXnode from the streamlet beginning at the specified position until thereare no more messages in the streamlet to send. When a new message ispublished to a streamlet, MX nodes that have subscribed to thatstreamlet will receive the new message. If a streamlet's TTL hasexpired, the handler process 351 can send an EOF message (392) to any MXnodes that are subscribed to the streamlet.

In some implementations, the messaging system 100 can include multipleconfiguration managers (e.g., configuration manager 214 plus one or moreother configuration managers). Multiple configuration managers canprovide resiliency and prevent single point of failure. For instance,one configuration manager can replicate lists of streamlets and currentgrants it maintains to another “slave” configuration manager. As anotherexample, multiple configuration managers can coordinate operationsbetween them using distributed consensus protocols, such as, forexample, Paxos or Raft protocols.

FIG. 4A is a data flow diagram of an example method for publishingmessages to a channel of a messaging system. In FIG. 4A, publishers(e.g., publisher clients 402, 404, 406) publish messages to themessaging system 100 described earlier in reference to FIG. 2. Forinstance, publishers 402 respectively establish connections 411 and sendpublish requests to the MX node 202. Publishers 404 respectivelyestablish connections 413 and send publish requests to the MX node 206.Publishers 406 respectively establish connections 415 and send publishrequests to the MX node 204. Here, the MX nodes can communicate (417)with a configuration manager (e.g., configuration manager 214) and oneor more Q nodes (e.g., Q nodes 212 and 208) in the messaging system 100via the internal network 218.

By way of illustration, each publish request (e.g., in JSON key/valuepairs) from a publisher to an MX node includes a channel name and amessage. The MX node (e.g., MX node 202) can assign the message in thepublish request to a distinct channel in the messaging system 100 basedon the channel name (e.g., “foo”) of the publish request. The MX nodecan confirm the assigned channel with the configuration manager 214. Ifthe channel (specified in the subscribe request) does not yet exist inthe messaging system 100, the configuration manager can create andmaintain a new channel in the messaging system 100. For instance, theconfiguration manager can maintain a new channel by maintaining a listidentifying each active streamlet of the channel's stream, therespective Q node on which the streamlet resides, and identification ofthe positions of the first and last messages in the streamlet asdescribed earlier.

For messages of a particular channel, the MX node can store the messagesin one or more buffers or streamlets in the messaging system 100. Forinstance, the MX node 202 receives from the publishers 402 requests topublish messages M11, M12, M13, and M14 to a channel foo. The MX node206 receives from the publishers 404 requests to publish messages M78and M79 to the channel foo. The MX node 204 receives from the publishers406 requests to publish messages M26, M27, M28, M29, M30, and M31 to thechannel foo.

The MX nodes can identify one or more streamlets for storing messagesfor the channel foo. As described earlier, each MX node can request awrite grant from the configuration manager 214 that allows the MX nodeto store the messages in a streamlet of the channel foo. For instance,the MX node 202 receives a grant from the configuration manager 214 towrite messages M11, M12, M13, and M14 to a streamlet 4101 on the Q node212. The MX node 206 receives a grant from the configuration manager 214to write messages M78 and M79 to the streamlet 4101. Here, the streamlet4101 is the last one (at the moment) of a sequence of streamlets of thechannel stream 430 storing messages of the channel foo. The streamlet4101 has messages (421) of the channel foo that were previously storedin the streamlet 4101, but is still open, i.e., the streamlet 4101 stillhas space for storing more messages and the streamlet's TTL has notexpired.

The MX node 202 can arrange the messages for the channel foo based onthe respective time that each message was received by the MX node 202,e.g., M11, M13, M14, M12 (422), and store the received messages asarranged in the streamlet 4101. That is, the MX node 202 receives M11first, followed by M13, M14, and M12. Similarly, the MX node 206 canarrange the messages for the channel foo based on their respective timethat each message was received by the MX node 206, e.g., M78, M79 (423),and store the received messages as arranged in the streamlet 4101. Otherarrangements or ordering of the messages for the channel are possible.

The MX node 202 (or MX node 206) can store the received messages usingthe method for writing data to a streamlet described earlier inreference to FIG. 3A, for example. In various implementations, the MXnode 202 (or MX node 206) can buffer (e.g., in a local data buffer) thereceived messages for the channel foo and store the received messages ina streamlet for the channel foo (e.g., streamlet 4101) when the bufferedmessages reach a predetermined number or size (e.g., 100 messages) orwhen a predetermined time (e.g., 50 milliseconds) has elapsed. Forinstance, the MX node 202 can store in the streamlet 100 messages at atime or in every 50 milliseconds. Other appropriate algorithms andtechniques, such as Nagle's algorithm, can be used for managing thebuffered messages.

In various implementations, the Q node 212 (e.g., a handler process)stores the messages of the channel foo in the streamlet 4101 in theorder as arranged by the MX node 202 and MX node 206. The Q node 212stores the messages of the channel foo in the streamlet 4101 in theorder the Q node 212 receives the messages. For instance, assume thatthe Q node 212 receives messages M78 (from the MX node 206) first,followed by messages M11 and M13 (from the MX node 202), M79 (from theMX node 206), and M14 and M12 (from the MX node 202). The Q node 212stores in the streamlet 4101 the messages in the order as received,e.g., M78, M11, M13, M79, M14, and M12, immediately after the messages421 that are already stored in the streamlet 4101. In this way, messagespublished to the channel foo from multiple publishers (e.g., 402, 404)can be serialized in a particular order and stored in the streamlet 4101of the channel foo. Different subscribers that subscribe to the channelfoo will receive messages of the channel foo in the same particularorder, as will be described in more detail in reference to FIG. 4B.

In the example of FIG. 4A, at a time instance after the message M12 wasstored in the streamlet 4101, the MX node 204 requests a grant from theconfiguration manager 214 to write to the channel foo. The configurationmanager 214 provides the MX node 204 a grant to write messages to thestreamlet 4101, as the streamlet 4101 is still open for writing. The MXnode 204 arranges the messages for the channel foo based on therespective time that each message was received by the MX node 204, e.g.,M26, M27, M31, M29, M30, M28 (424), and stores the messages as arrangedfor the channel foo.

By way of illustration, assume that the message M26 is stored to thelast available position of the streamlet 4101. As the streamlet 4101 isnow full, the Q node 212 sends to the MX node 204 a NAK message,following by an EOF message, to close the association with the MX node204 for the write grant, as described earlier in reference to FIG. 3A.The MX node 204 then requests another write grant from the configurationmanager 214 for additional messages (e.g., M27, M31, and so on) for thechannel foo.

The configuration manager 214 can monitor available Q nodes in themessaging system 100 for their respective workloads (e.g., how manystreamlets are residing in each Q node). The configuration manager 214can allocate a streamlet for the write request from the MX node 204 suchthat overloading (e.g., too many streamlets or too many read or writegrants) can be avoided for any given Q node. For instance, theconfiguration manager 214 can identify a least loaded Q node in themessaging system 100 and allocate a new streamlet on the least loaded Qnode for write requests from the MX node 204. In the example of FIG. 4A,the configuration manager 214 allocates a new streamlet 4102 on the Qnode 208 and provides a write grant to the MX node 204 to write messagesfor the channel foo to the streamlet 4102. As shown in FIG. 4A, the Qnode stores in the streamlet 4102 the messages from the MX node 204 inan order as arranged by the MX node 204: M27, M31, M29, M30, and M28(assuming that there is no other concurrent write grant for thestreamlet 4102 at the moment).

When the configuration manager 214 allocates a new streamlet (e.g.,streamlet 4102) for a request for a grant from an MX node (e.g., MX node204) to write to a channel (e.g., foo), the configuration manager 214assigns to the streamlet its TTL, which will expire after TTLs of otherstreamlets that are already in the channel's stream. For instance, theconfiguration manager 214 can assign to each streamlet of the channelfoo's channel stream a TTL of 3 minutes when allocating the streamlet.That is, each streamlet will expire 3 minutes after it is allocated(created) by the configuration manager 214. Since a new streamlet isallocated after a previous streamlet is closed (e.g., filled entirely orexpired), in this way, the channel foo's channel stream comprisesstreamlets that each expires sequentially after its previous streamletexpires. For instance, as shown in an example channel stream 430 of thechannel foo in FIG. 4A, streamlet 4098 and streamlets before 4098 haveexpired (as indicated by the dotted-lined gray-out boxes). Messagesstored in these expired streamlets are not available for reading forsubscribers of the channel foo. Streamlets 4099, 4100, 4101, and 4102are still active (not expired). The streamlets 4099, 4100, and 4101 areclosed for writing, but still are available for reading. The streamlet4102 is available for reading and writing, at the moment when themessage M28 was stored in the streamlet 4102. At a later time, thestreamlet 4099 will expire, following by the streamlets 4100, 4101, andso on.

FIG. 4B is a data flow diagram of an example method for subscribing to achannel of a messaging system. In FIG. 4B, a subscriber 480 establishesa connection 462 with an MX node 461 of the messaging system 100.Subscriber 482 establishes a connection 463 with the MX node 461.Subscriber 485 establishes a connection 467 with an MX node 468 of themessaging system 100. Here, the MX nodes 461 and 468 can respectivelycommunicate (464) with the configuration manager 214 and one or more Qnodes in the messaging system 100 via the internal network 218.

A subscriber (e.g., subscriber 480) can subscribe to the channel foo ofthe messaging system 100 by establishing a connection (e.g., 462) andsending a request for subscribing to messages of the channel foo to anMX node (e.g., MX node 461). The request (e.g., in JSON key/value pairs)can include a channel name, such as, for example, “foo.” When receivingthe subscribe request, the MX node 461 can send to the configurationmanager 214 a request for a read grant for a streamlet in the channelfoo's channel stream.

By way of illustration, assume that at the current moment the channelfoo's channel stream 431 includes active streamlets 4102, 4103, and4104, as shown in FIG. 4B. The streamlets 4102 and 4103 each are full.The streamlet 4104 stores messages of the channel foo, including thelast message (at the current moment) stored at a position 47731.Streamlets 4101 and streamlets before 4101 are invalid, as theirrespective TTLs have expired. Note that the messages M78, M11, M13, M79,M14, M12, and M26 stored in the streamlet 4101, described earlier inreference to FIG. 4A, are no longer available for subscribers of thechannel foo, since the streamlet 4101 is no longer valid, as its TTL hasexpired. As described earlier, each streamlet in the channel foo'schannel stream has a TTL of 3 minutes, thus only messages (as stored instreamlets of the channel foo) that are published to the channel foo(i.e., stored into the channel's streamlets) no earlier than 3 minutesfrom the current time can be available for subscribers of the channelfoo.

The MX node 461 can request a read grant for all available messages inthe channel foo, for example, when the subscriber 480 is a newsubscriber to the channel foo. Based on the request, the configurationmanager 214 provides the MX node 461 a read grant to the streamlet 4102(on the Q node 208) that is the earliest streamlet in the activestreamlets of the channel foo (i.e., the first in the sequence of theactive streamlets). The MX node 461 can retrieve messages in thestreamlet 4102 from the Q node 208, using the method for reading datafrom a streamlet described earlier in reference to FIG. 3B, for example.Note that the messages retrieved from the streamlet 4102 maintain thesame order as stored in the streamlet 4102. However, other arrangementsor ordering of the messages in the streamlet are possible. In variousimplementations, when providing messages stored in the streamlet 4102 tothe MX node 461, the Q node 208 can buffer (e.g., in a local databuffer) the messages and send the messages to the MX node 461 when thebuffer messages reach a predetermined number or size (e.g., 200messages) or a predetermined time (e.g., 50 milliseconds) has elapsed.For instance, the Q node 208 can send the channel foo's messages (fromthe streamlet 4102) to the MX node 461 200 messages at a time or inevery 50 milliseconds. Other appropriate algorithms and techniques, suchas Nagle's algorithm, can be used for managing the buffered messages.

After receiving the last message in the streamlet 4102, the MX node 461can send an acknowledgement to the Q node 208, and send to theconfiguration manager 214 another request (e.g., for a read grant) forthe next streamlet in the channel stream of the channel foo. Based onthe request, the configuration manager 214 provides the MX node 461 aread grant to the streamlet 4103 (on Q node 472) that logically followsthe streamlet 4102 in the sequence of active streamlets of the channelfoo. The MX node 461 can retrieve messages stored in the streamlet 4103,e.g., using the method for reading data from a streamlet describedearlier in reference to FIG. 3B, until it retrieves the last messagestored in the streamlet 4103. The MX node 461 can send to theconfiguration manager 214 yet another request for a read grant formessages in the next streamlet 4104 (on Q node 474). After receiving theread grant, the MX node 461 retrieves messages of the channel foo storedin the streamlet 4104, until the last message at the position 47731.Similarly, the MX node 468 can retrieve messages from the streamlets4102, 4103, and 4104 (as shown with dotted arrows in FIG. 4B), andprovide the messages to the subscriber 485.

The MX node 461 can send the retrieved messages of the channel foo tothe subscriber 480 (via the connection 462) while receiving the messagesfrom the Q nodes 208, 472, or 474. In various implementations, the MXnode 461 can store the retrieved messages in a local buffer. In thisway, the retrieved messages can be provided to another subscriber (e.g.,subscriber 482) when the other subscriber subscribes to the channel fooand requests the channel's messages. The MX node 461 can remove messagesstored in the local buffer that each has a time of publication that hasexceeded a predetermined time period. For instance, the MX node 461 canremove messages (stored in the local buffer) with respective times ofpublication exceeding 3 minutes. In some implementations, thepredetermined time period for keeping messages in the local buffer on MXnode 461 can be the same as or similar to the time-to-live duration of astreamlet in the channel foo's channel stream, since at a given moment,messages retrieved from the channel's stream do not include those instreamlets having respective times-to-live that had already expired.

The messages retrieved from the channel stream 431 and sent to thesubscriber 480 (by the MX node 461) are arranged in the same order asthe messages were stored in the channel stream, although otherarrangements or ordering of the messages are possible. For instance,messages published to the channel foo are serialized and stored in thestreamlet 4102 in a particular order (e.g., M27, M31, M29, M30, and soon), then stored subsequently in the streamlet 4103 and the streamlet4104. The MX node retrieves messages from the channel stream 431 andprovides the retrieved messages to the subscriber 480 in the same orderas the messages are stored in the channel stream: M27, M31, M29, M30,and so on, followed by ordered messages in the streamlet 4103, andfollowed by ordered messages in the streamlet 4104.

Instead of retrieving all available messages in the channel stream 431,the MX node 461 can request a read grant for messages stored in thechannel stream 431 starting from a message at particular position, e.g.,position 47202. For instance, the position 47202 can correspond to anearlier time instance (e.g., 10 seconds before the current time) whenthe subscriber 480 was last subscribing to the channel foo (e.g., via aconnection to the MX node 461 or another MX node of the messaging system100). The MX node 461 can send to the configuration manager 214 arequest for a read grant for messages starting at the position 47202.Based on the request, the configuration manager 214 provides the MX node461 a read grant to the streamlet 4104 (on the Q node 474) and aposition on the streamlet 4104 that corresponds to the channel streamposition 47202. The MX node 461 can retrieve messages in the streamlet4104 starting from the provided position, and send the retrievedmessages to the subscriber 480.

As described above in reference to FIGS. 4A and 4B, messages publishedto the channel foo are serialized and stored in the channel's streamletsin a particular order. The configuration manager 214 maintains theordered sequence of streamlets as they are created throughout theirrespective times-to-live. Messages retrieved from the streamlets by anMX node (e.g., MX node 461, or MX node 468) and provided to a subscribercan be, in some implementations, in the same order as the messages arestored in the ordered sequence of streamlets. In this way, messages sentto different subscribers (e.g., subscriber 480, subscriber 482, orsubscriber 485) can be in the same order (as the messages are stored inthe streamlets), regardless which MX nodes the subscribers are connectedto.

In various implementations, a streamlet stores messages in a set ofblocks of messages. Each block stores a number of messages. Forinstance, a block can store two hundred kilobytes of messages (althoughother sizes of blocks of messages are possible). Each block has its owntime-to-live, which can be shorter than the time-to-live of thestreamlet holding the block. Once a block's TTL has expired, the blockcan be discarded from the streamlet holding the block, as described inmore detail below in reference to FIG. 4C.

FIG. 4C is an example data structure for storing messages of a channelof a messaging system. As described with the channel foo in reference toFIGS. 4A and 4B, assume that at the current moment the channel foo'schannel stream 432 includes active streamlets 4104 and 4105, as shown inFIG. 4C. Streamlet 4103 and streamlets before 4103 are invalid, as theirrespective TTLs have expired. The streamlet 4104 is already full for itscapacity (e.g., as determined by a corresponding write grant) and isclosed for additional message writes. The streamlet 4104 is stillavailable for message reads. The streamlet 4105 is open and is availablefor message writes and reads.

By way of illustration, the streamlet 4104 (e.g., a computing processrunning on the Q node 474 shown in FIG. 4B) currently holds two blocksof messages. Block 494 holds messages from channel positions 47301 to47850. Block 495 holds messages from channel positions 47851 to 48000.The streamlet 4105 (e.g., a computing process running on another Q nodein the messaging system 100) currently holds two blocks of messages.Block 496 holds messages from channel positions 48001 to 48200. Block497 holds messages starting from channel position 48201, and stillaccepts additional messages of the channel foo.

When the streamlet 4104 was created (e.g., by a write grant), a firstblock (sub-buffer) 492 was created to store messages, e.g., from channelpositions 47010 to 47100. Later on, after the block 492 had reached itscapacity, another block 493 was created to store messages, e.g., fromchannel positions 47111 to 47300. Blocks 494 and 495 were subsequentlycreated to store additional messages. Afterwards, the streamlet 4104 wasclosed for additional message writes, and the streamlet 4105 was createdwith additional blocks for storing additional messages of the channelfoo.

In this example, the respective TTL's of blocks 492 and 493 had expired.The messages stored in these two blocks (from channel positions 47010 to47300) are no longer available for reading by subscribers of the channelfoo. The streamlet 4104 can discard these two expired blocks, e.g., byde-allocating the memory space for the blocks 492 and 493. The blocks494 or 495 could become expired and be discarded by the streamlet 4104,before the streamlet 4104 itself becomes invalid. Alternatively,streamlet 4104 itself could become invalid before the blocks 494 or 495become expired. In this way, a streamlet can hold one or more blocks ofmessages, or contain no block of messages, depending on respective TTLsof the streamlet and blocks, for example.

A streamlet, or a computing process running on a Q node in the messagingsystem 100, can create a block for storing messages of a channel byallocating a certain size of memory space from the Q node. The streamletcan receive, from an MX node in the messaging system 100, one message ata time and store the received message in the block. Alternatively, theMX node can assemble (i.e., buffer) a group of messages and send thegroup of messages to the Q node. The streamlet can allocate a block ofmemory space (from the Q node) and store the group of messages in theblock. The MX node can also perform compression on the group ofmessages, e.g., by removing a common header from each message orperforming other suitable compression techniques.

As described above, a streamlet (a data buffer) residing on a Q nodestores messages of a channel in the messaging system 100. To preventfailure of the Q node (a single point failure) that can cause messagesbeing lost, the messaging system 100 can replicate messages on multipleQ nodes, as described in more detail below.

FIG. 5A is a data flow diagram of an example method 500 for publishingand replicating messages of the messaging system 100. As describedearlier in reference to FIG. 4A, the MX node 204 receives messages (ofthe channel foo) from the publishers 406. The configuration manager 214can instruct the MX Node 204 (e.g., with a write grant) to store themessages in the streamlet 4102 on the Q node 208. In FIG. 5A, instead ofstoring the messages on a single node (e.g., Q node 208), theconfiguration manager 214 allocates multiple Q nodes to store multiplecopies of the streamlet 4102 on these Q nodes.

By way of illustration, the configuration manager 214 allocates Q nodes208, 502, 504, and 506 in the messaging system 100 to store copies ofthe streamlet 4102. The configuration manager 214 instructs the MX node204 to transmit the messages for the channel foo (e.g., messages M27,M31, M29, M30, and M28) to the Q node 208 (512). A computing processrunning on the Q node 208 stores the messages in the first copy (copy#1) of the streamlet 4102. Instead of sending an acknowledgement messageto the MX node 204 after storing the messages, the Q node 208 forwardsthe messages to the Q node 502 (514). A computing process running on theQ node 502 stores the messages in another copy (copy #2) of thestreamlet 4102. Meanwhile, the Q node 502 forwards the messages to the Qnode 504 (516). A computing process running on the Q node 504 stores themessages in yet another copy (copy #3) of the streamlet 4102. The Q node504 also forwards the message to the Q node 506 (518). A computingprocess running on the Q node 506 stores the messages in yet anothercopy (copy #4) of the streamlet 4102. The Q node 506 can send anacknowledgement message to the MX node 204, indicating that all themessages (M27, M31, M29, M30, and M28) have been stored successfully instreamlet copies #1, #2, #3 and #4.

In some implementations, after successfully storing the last copy (copy#4), the Q node 506 can send an acknowledgement to its upstream Q node(504), which in turns sends an acknowledgement to its upstream Q node(502), and so on, until the acknowledgement is sent to the Q node 208storing the first copy (copy #1). The Q node 208 can send anacknowledgement message to the MX node 204, indicating that all messageshave been stored successfully in the streamlet 4102 (i.e., in the copies#1, #2, #3 and #4).

In this way, four copies of the streamlet 4102 (and each message in thestreamlet) are stored in four different Q nodes. Other numbers (e.g.,two, three, five, or other suitable number) of copies of a streamlet arealso possible. In the present illustration, the four copies form a chainof copies including a head copy in the copy #1 and a tail copy in thecopy #4. When a new message is published to the streamlet 4102, themessage is first stored in the head copy (copy #1) on the Q node 208.The message is then forwarded downstream to the next adjacent copy, thecopy #2 on the Q node 502 for storage, then to the copy #3 on the Q node504 for storage, until the message is stored in the tail copy the copy#4 on the Q node 506.

In addition to storing and forwarding by messages, the computingprocesses running on Q nodes that store copies of a streamlet can alsostore and forward messages by blocks of messages, as described earlierin reference to FIG. 4C. For instance, the computing process storing thecopy #1 of the streamlet 4102 on Q node 208 can allocate memory andstore a block of, for example, 200 kilobytes of messages (although othersizes of blocks of messages are possible), and forward the block ofmessages to the next adjacent copy (copy #2) of the chain for storage,and so on, until the block messages is stored in the tail copy (copy #4)on the Q node 506.

Messages of the streamlet 4102 can be retrieved and delivered to asubscriber of the channel foo from one of the copies of the streamlet4102. FIG. 5B is a data flow diagram of an example method 550 forretrieving stored messages in the messaging system 100. For instance,the subscriber 480 can send a request for subscribing to messages of thechannel to the MX node 461, as described earlier in reference to FIG.4B. The configuration manager 214 can provide to the MX node 461 a readgrant for one of the copies of the streamlet 4102. The MX node 461 canretrieve messages of the streamlet 4102 from one of the Q nodes storinga copy of the streamlet 4102, and provide the retrieved messages to thesubscriber 480. For instance, the MX node 461 can retrieve messages fromthe copy #4 (the tail copy) stored on the Q node 506 (522). As foranother example, the MX node 461 can retrieve messages from the copy #2stored on the Q node 502 (524). In this way, the multiple copies of astreamlet (e.g., copies #1, #2, #3, and #4 of the streamlet 4102)provide replication and redundancy against failure if only one copy ofthe streamlet were stored in the messaging system 100. In variousimplementations, the configuration manager 214 can balance workloadsamong the Q nodes storing copies of the streamlet 4102 by directing theMX node 461 (e.g., with a read grant) to a particular Q node that has,for example, less current read and write grants as compared to other Qnodes storing copies of the streamlet 4102.

A Q node storing a particular copy in a chain of copies of a streamletmay fail, e.g., a computing process on the Q node storing the particularcopy may freeze. Other failure modes of a Q node are possible. An MXnode can detect a failed node (e.g., from non-responsiveness of thefailed node) and report the failed node to a configuration manager inthe messaging system 100 (e.g., configuration manager 214). A peer Qnode can also detect a failed Q node and report the failed node to theconfiguration manager. For instance, an upstream Q node may detect afailed downstream Q node when the downstream Q node is non-responsive,e.g., fails to acknowledge a message storage request from the upstream Qnode as described earlier. It is noted that failure of a Q node storinga copy of a particular streamlet of a particular channel stream does nothave to be for publish or subscribe operations of the particularstreamlet or of the particular channel stream. Failure stemming fromoperations on another streamlet or another channel stream can also alerta configuration manager about failure of a Q node in the messagingsystem 100.

When a Q node storing a particular copy in a chain of copies of astreamlet fails, a configuration manager in the messaging system 100 canrepair the chain by removing the failed node, or by inserting a new nodefor a new copy into the chain, for example. FIGS. 5C and 5D are dataflow diagrams of example methods for repairing a chain of copies of astreamlet in the messaging system 100. In FIG. 5C, for instance, afterdetecting that the Q node 504 fails, the configuration manager 214 canrepair the chain of copies by redirecting messages intended to be storedin the copy #3 of the streamlet 4102 on the Q node 502 to the copy #4 ofthe streamlet 4102 on the Q node 506. In this example, a message (or ablock of messages) is first sent from the MX node 204 to the Q node 208for storage in the copy #1 of the streamlet 4102 (572). The message thenis forwarded to the Q node 502 for storage in the copy #2 of thestreamlet 4102 (574). The message is then forwarded to the Q node 506for storage in the copy #4 of the streamlet 4102 (576). The Q node 506can send an acknowledgement message to the configuration manager 214indicating that the message has been stored successfully.

Here, a failed node can also be the node storing the head copy or thetail copy of the chain of copies. For instance, if the Q node 208 fails,the configuration manager 214 can instruct the MX node 204 first to sendthe message to the Q node 502 for storage in the copy #2 of thestreamlet 4102. The message is then forwarded to the next adjacent copyin the chain for storage, until the message is stored in the tail copy.

If the Q node 506 fails, the configuration manager 214 can repair thechain of copies of the streamlet 4102 such that the copy #3 on the Qnode 504 becomes the tail copy of the chain. A message is first storedin the copy #1 on the Q node 208, then subsequently stored in the copy#2 on the Q node 502, and the copy #3 on the Q node 504. The Q node 504then can send an acknowledgement message to the configuration manager214 indicating that the message has been stored successfully.

In FIG. 5D, the configuration manager 214 replaces the failed node Qnode 504 by allocating a new Q node 508 to store a copy #5 of the chainof copies of the streamlet 4102. In this example, the configurationmanager 214 instructs the MX node 204 to send a message (from thepublishers 406) to the Q node 208 for storage in the copy #1 of thestreamlet 4102 (582). The message is then forwarded to the Q node 502for storage in the copy #2 of the streamlet 4102 (584). The message isthen forwarded to the Q node 508 for storage in the copy #5 of thestreamlet 4012 (586). The message is then forwarded to the Q node 506for storage in the copy #4 of the streamlet 4102 (588). The Q node 506can send an acknowledgement message to the configuration manager 214indicating that the message has been stored successfully.

FIG. 6 is a data flow diagram 600 illustrating the application ofselective filtering, searching, transforming, querying, aggregating andtransforming of messages in real time to manage the delivery of messagesinto and through each channel and on to individual subscribers. Usersoperating applications on client devices, such as, for example,smartphones, tablets, and other internet-connected devices, act assubscribers (e.g., subscriber 480 in FIG. 4B, subscriber 602 in FIG. 6).The applications may be, for example, consumers of the messages toprovide real-time information about news, transportation, sports,weather, or other subjects that rely on published messages attributed toone or more subjects and/or channels. Message publishers 604 can be anyinternet-connected service that provides, for example, status data,transactional data or other information that is made available to thesubscribers 602 on a subscription basis. In some versions, therelationship between publishers and channels is 1:1, such that is thereis one and only one publisher that provides messages into thatparticular channel. In other instances, the relationship may bemany-to-one (more than one publisher provides messages into a channel),one-to-many (a publisher's messages are sent to more than one channel),or many-to-many (more than one publisher provides messages to more thanone channel). Typically, when a subscriber subscribes to a channel, theyreceive all messages and all message data published to the channel assoon as it is published. The result, however, is that many subscriberscan receive more data (or data that requires further processing) than isuseful. The additional filtering or application of functions against thedata places undue processing requirements on the subscriber applicationand can delay presentation of the data in its preferred format.

A filter 606 can be created by providing suitable query instructions at,for example, the time the subscriber 602 subscribes to the channel 608.The filter 606 that is specified can be applied to all messagespublished to the channel 608 (e.g., one message at a time), and can beevaluated before the subscriber 602 receives the messages (e.g., block 2in FIG. 6). By allowing subscribers 602 to create query instructions apriori, that is upon subscribing to the channel 608 and before data isreceived into the channel 608, the burden of filtering and processingmessages moves closer to the data source, and can be managed at thechannel level. As a result, the messages are pre-filtered and/orpre-processed before they are forwarded to the subscriber 602. Again,the query instructions need not be based on any a priori knowledge ofthe form or substance of the incoming messages. The query instructionscan be used to pre-process data for applications such as, for example,real-time monitoring services (for transportation, healthcare, news,sports, weather, etc.) and dashboards (e.g., industrial monitoringapplications, financial markets, etc.) to filter data, summarize dataand/or detect anomalies. One or more filters 606 can be applied to eachchannel 608.

The query instructions can implement real-time searches and queries,aggregate or summarize data, or transform data for use by a subscriberapplication. In some embodiments, including those implementing JSONformatted messages, the messages can be generated, parsed andinterpreted using the query instructions, and the lack of a pre-definedschema (unlike conventional RDBMS/SQL-based applications) means that thequery instructions can adapt to changing business needs without the needfor schema or application layer changes. This allows the queryinstructions to be applied selectively at the message level within achannel, thus filtering and/or aggregating messages within the channel.In some instances, the queries may be applied at the publisherlevel—meaning channels that receive messages from more than onepublisher may apply certain filters against messages from specificpublishers. The query instructions may be applied on a going-forwardbasis, that is on only newly arriving messages, and/or in some cases,the query instructions may be applied to historical messages alreadyresiding in the channel queue.

The query instructions can be applied at either or both of the ingressand egress side of the PubSub service. On the egress side, the queryinstructions act as a per-connection filter against the messagechannels, and allow each subscriber to manage their own set of uniquefilters. On the ingress side, the query instructions operate as acentralized, system-wide filter that is applied to all publishedmessages.

For purposes of illustration and not limitation, examples of queryinstructions that may be applied during message ingress include:

-   -   A message may be distributed to multiple channels or to a        different channel (e.g., based on geo-location in the message,        or based on a hash function of some value in the message).    -   A message may be dropped due to spam filtering or DoS rules        (e.g., limiting the number of messages a publisher can send in a        given time period).    -   An alert message may be sent to an admin channel on some event        arriving at any channel (e.g., cpu_temp>threshold).

For purposes of illustration and not limitation, examples of queryinstructions that may be applied during message egress include:

-   -   Channels that contain events from various sensors where the user        is only interested in a subset of the data sources.    -   Simple aggregations, where a system reports real time events,        such as cpu usage, sensor temperatures, etc., and we would like        to receive some form of aggregation over a short time period,        irrespective of the number of devices reporting or the reporting        frequency, e.g., average (cpu_load), max(temperature),        count(number_of_users), count(number_of_messages) group by        country.    -   Transforms, where a system reports real time events and metadata        is added to them from mostly static external tables, e.g.,        adding a city name based on IP address, converting an        advertisement ID to a marketing campaign ID or to a marketing        partner ID.    -   Adding default values to event streams where such values do not        exist on certain devices.    -   Advanced aggregations, where a system reports real time events,        and combines some mostly static external table data into the        aggregation in real time, e.g., grouping advertisement clicks by        partners and counting number of events.    -   Counting number of user events, grouping by a/b test cell        allocation.

In some embodiments, the query instructions may be used to define anindex or other suitable temporary data structure, which may then beapplied against the messages as they are received into the channel toallow for the reuse of the data element(s) as searchable elements. Insuch cases, a query frequency may be maintained to describe the numberof times (general, or in a given period) that a particular data elementis referred to or how that element is used. If the frequency that thedata element is used in a query exceeds some threshold, the index may bestored for subsequent use on incoming messages, whereas in otherinstances in which the index is used only once (or infrequently) it maybe discarded. In some instances, the query instruction may be applied tomessages having arrived at the channel prior to the creation of theindex. Thus, the messages are not indexed according to the data elementsdescribed in the query instructions but processed using the queryinstructions regardless, whereas messages arriving after the creation ofthe index may be filtered and processed using the index. For queries orother subscriptions that span the time at which the index may have beencreated, the results of applying the query instructions to the messagesas they are received and processed with the index may be combined withresults of applying the query instructions to non-indexed messagesreceived prior to receipt of the query instructions.

For purposes of illustration and not limitation, one use case for such afiltering application is a mapping application that subscribes to publictransportation data feeds, such as the locations of all buses across acity. The published messages may include, for example, geographic datadescribing the location, status, bus agency, ID number, route number,and route name of the buses. Absent pre-defined query instructions, theclient application would receive individual messages for all buses.However, query instructions may be provided that filter out, forexample, inactive routes and buses and aggregate, for example, a countof buses by agency. The subscriber application receives the filtered busdata in real time and can create reports, charts and other user-definedpresentations of the data. When new data is published to the channel,the reports can be updated in real time based on a period parameter(described in more detail below).

The query instructions can be provided (e.g., at the time the subscribersubscribes to the channel) in any suitable format or syntax. Forexample, the following illustrates the structure of several fields of asample subscription request Protocol Data Unit (PDU) with the PDU keysspecific to adding a filter to a subscription request:

{

-   -   “action”: “subscribe”,    -   “body”: {        -   “channel”: “ChannelName”        -   “filter”: “QueryInstructions”        -   “period”: [1-60, OPTIONAL]    -   }

}

In the above subscription request PDU, the “channel” field can be avalue (e.g., string or other appropriate value or designation) for thename of the channel to which the subscriber wants to subscribe. The“filter” field can provide the query instructions or other suitablefilter commands, statements, or syntax that define the type ofkey/values in the channel message to return to the subscriber. The“period” parameter specifies the time period in, for example, seconds,to retain messages before returning them to the subscriber (e.g., aninteger value from 1 to 60, with a default of, for example, 1). The“period” parameter will be discussed in more detail below. It is notedthat a subscription request PDU can include any other suitable fields,parameters, or values.

One example of a query instruction is a “select” filter, which selectsthe most recent (or “top”) value for all (e.g., “select.*”) or selected(e.g., “select.name”) data elements. In the example below, the Filtercolumn shows the filter value sent in the query instructions as part ofa subscription as the filter field. The Message Data column lists theinput of the channel message data and the message data sent to theclient as output. In this example, the value for the “extra” key doesnot appear in the output, as the “select” filter can return only thefirst level of results and does not return any nested key values.

Filter Message Data SELECT * Input {″name″: ″art″, ″eye″: ″blue″},{″name″: ″art″, ″age″: 11}, {″age″: 12, ″height″: 190} Output {″name″:″art″, ″age″: 12, ″eye″: ″blue″, ″height″: 190} SELECT Input top.*{″top″: {″age″: 12, ″eyes″: ″blue″}}, {″top″: {″name″: ″joy″, ″height″:168}, ″extra.″: 1}, {″top″: {″name″: ″art″}} Output {″name″: ″art″,″age″: 12, ″eye″: ″blue″, ″height″: 168}

For aggregative functions, all messages can be combined that satisfy thequery instructions included in the GROUP BY clause. The aggregatedvalues can then be published as a single message to the subscriber(s) atthe end of the aggregation period. The number of messages that areaggregated depends on, for example, the number_of_messages received inthe channel in the period value for the filter. For instance, if theperiod parameter is set to 1, and 100 messages are received in onesecond, all 100 messages are aggregated into a single message fortransmission to the subscsriber(s). As an example, a query instructionas shown below includes a filter to aggregate position data for anobject, grouping it by obj_id, with a period of 1:

-   -   SELECT * WHERE (<expression with aggregate function>) GROUP BY        obj_id        In this example, all messages published in the previous second        with the same obj_id are grouped and sent as a batch to the        subscriber(s).

In some embodiments, a MERGE(*) function can be used to change howaggregated message data is merged. The MERGE(*) function can return arecursive union of incoming messages over a period of time. The mergefunction may be used, for example, to track location data for an object,and the subscriber is interested in the most recent values for allkey/value pairs contained in a set of aggregated messages. The followingstatement shows an exemplary syntax for the MERGE(*) function:

-   -   SELECT [expr] [name,]MERGE(*)[.*] [AS name] [FROM expr] [WHERE        expr] [HAVING expr] GROUP BY name

The following examples illustrate how the MERGE(*) function may beapplied within query instructions to various types of channel messages.In the following examples, the Filter column shows the filter valueincluded in the query instructions as part of a subscription request asthe FILTER field. The Message Data column lists the Input channelmessage data and the resulting message data sent to the subscriber asOutput. The filter returns the most recent values of the keys identifiedin the input messages, with the string MERGE identified as the columnname in the output message data. The first example below shows theMERGE(*) function in a filter with a wildcard, for the message data isreturned using the keys from the input as column names in the output.

Filter Message Data SELECT Input MERGE(*) {″name″: ″art″, ″age″: 10},{″name″: ″art″, ″age″: 11, ″items″: [0]} Output {″MERGE″: {″name″:″art″, ″age″: 11, ″items″: [0]}}The next example illustrates the use of the MERGE(*) function in afilter using a wildcard and the “AS” statement with a value of MERGE.The output data includes MERGE as the column name.

Filter Message Data SELECT Input MERGE(*).* {  ″name″: ″art″,  ″age″:12,  ″items″: [0],  ″skills″: {   ″work″: [″robots″]  } }, {  ″name″:″art″,  ″age″: 13,  ″items″: [″car″],  ″skills″: {   ″home″: [″cooking″] } } Output {  ″name″: ″art″,  ″age″: 13,  ″items″: [″car″],  ″skills″:{   ″work″: [″robots″],   ″home″: [″cooking″]  } } SELECT Input MERGE{″top″: { }, ″garbage″: 0}, (top.*) AS {″top″: {″name″: ″art″, ″eyes″:″blue″}}, merge {″top″: (″name″: ″joy″, ″height″: 170}} Output {″merge″:{″name″: ″joy″, ″eyes″: ″blue″, ″height″: 170}}

Generally, for aggregative functions and for filters that only include aSELECT(expr) statement, only the latest value for any JSON key in themessage data from the last message received can be stored and returned.Therefore, if the most recent message received that satisfies the filterstatement is missing a key value identified in a previously processedmessage, that value is not included in the aggregate, which could resultin data loss. However, filters that also include the MERGE(*) functioncan retain the most recent value for all keys that appear in messages toan unlimited JSON object depth. Accordingly, the most recent version ofall key values can be retained in the aggregate.

The MERGE(*) function can be used to ensure that associated values forall keys that appear in any message during the aggregation period alsoappear in the final aggregated message. For example, a channel may trackthe physical location of an object in three dimensions: x, y, and z.During an aggregation period of one second, two messages are publishedto the channel, one having only two parameters: OBJ{x:1, y:2, z:3} andOBJ{x:2, y:3}. In the second message, the z value did not change and wasnot included in the second message. Without the MERGE(*) function, theoutput result would be OBJ{x:2, y:3}. Because the z value was notpresent in the last message in the aggregation period, the z value wasnot included in the final aggregate. However, with the MERGE(*)function, the result is OBJ{x:2, y:3, z:3}.

The following table shows one set of rules that may be used to aggregatedata in messages, depending on the type of data. For arrays, elementsneed not be merged, but instead JSON values can be overwritten for thearray in the aggregate with the last array value received.

Type of Data to Aggregate Without With JSON Data {msg1}, {msg2} MERGE(*)MERGE(*) Additional {a: 1, b: 2}, {c:3} {c: 3} {a:1, b:2, c:3} key/valueDifferent value {a:2}, {a: ″2″} {a:″2″} {a:″2″} datatype Missingkey/value {a:2}, { } {a:2} {a:2} null value {a:2}, {a:null} {a:null}{a:null} Different key value {a:{b:1}}, {a:{c:2}} {a:{c:2}} {a:{b:1,c:2}} Arrays {a:[1, 2]}, {a:[3, 4]} {a:[3, 4]} {a:[3, 4]}

The query instructions can be comprised of one or more suitable filtercommands, statements, functions, or syntax. For purposes of illustrationand not limitation, in addition to the SELECT and MERGE functions, thequery instructions can include filter statements or functions, such as,for example, ABS(expr), AVG(expr), COALESCE(a[, b . . . ]), CONCAT(a[, b. . . ]), COUNT(expr), COUNT_DISTINCT(expr), IFNULL(expr1, expr2),JSON(expr), MIN(expr[, expr1, . . .]), MAX(expr[, expr1, . . .]),SUBSTR(expr, expr1[, expr2]), SUM(expr), MD5(expr), SHA1(expr),FIRST_VALUE(expr) OVER (ORDER BY expr1), and/or LAST_VALUE(expr) OVER(ORDER BY expr1), where “expr” can be any suitable expression that iscapable of being processed by a filter statement or function, such as,for example, a SQL or SQL-like expression. Other suitable filtercommands, statements, functions, or syntax are possible for the queryinstructions.

According to the present invention, non-filtered queries can translateto an immediate copy of the message to the subscriber, without any JSONor other like processing. Queries that include a SELECT filter command(without aggregation) can translate into an immediate filter. Ininstances in which the messages are formatted using JSON, each messagemay be individually parsed and any WHERE clause may be executed directlyon the individual message as it arrives, without the need for creatingindices or other temporary data structures. If the messages pass theWHERE clause filter, the SELECT clause results in a filtered messagethat can be converted back to its original format or structure (e.g.,JSON) and sent to the subscriber.

Aggregative functions, such as, for example, COUNT( ), SUM( ), AVG( ),and the like, can translate into an immediate aggregator. In instancesin which the messages are formatted using JSON, each message may beindividually parsed and any WHERE clause may be executed directly on theindividual message as it arrives, without the need for creating indicesor other temporary data structures. If a WHERE clause is evaluated,messages passing such criteria are aggregated (e.g., aggregates in theSELECT clause are executed, thereby accumulating COUNT, SUM, AVG, and soforth) using the previous accumulated value and the value from theindividual message. Once per aggregation period (e.g., every 1 second),the aggregates are computed (e.g., AVG=SUM/COUNT), and the SELECT clauseoutputs the aggregated message, which can be converted to its originalformat or structure (e.g., JSON) and sent to the subscriber.

More complex aggregative functions, such as, for example, GROUP BY,JOIN, HAVING, and the like, can be translated into a hash tableaggregator. Unlike SELECT or other like functions that can use aconstant memory, linearly expanding memory requirements can be dependentupon the results of the GROUP BY clause. At most, grouping by a uniquevalue (e.g., SSN, etc.) can result in a group for each individualmessage, but in most cases grouping by a common data element (e.g.,user_id or other repeating value) can result in far fewer groups. Inpractice, each message is parsed (from its JSON format, for example).The WHERE clause can be executed directly on the individual message asit arrives, without creating indices or other temporary structures. Ifthe WHERE clause is satisfied, the GROUP BY expressions can be computeddirectly and used to build a hash key for the group. The aggregativefunctions in the SELECT clause can be executed, accumulating COUNT, SUM,AVG, or other functions using the previous accumulated value specificfor the hash key (group) and the value from the individual message. Onceper aggregation period (e.g., every 1 second), the aggregates arecomputed (e.g., AVG=SUM/COUNT) for each hash key (group), and the SELECTclause can output the aggregated message for each hash key to beconverted back to its original format or structure (e.g., JSON) and sentto the subscriber (e.g., one message per hash key (group)).

In embodiments in which the aggregation period is limited (e.g., 1second-60 seconds) and the network card or other hardware/throughputspeeds may be limited (e.g., 10/gbps), the overall maximal memoryconsumption can be calculated as time*speed (e.g., 1 GB per second, or60 GB per minute). Hence, the upper bound is independent of the numberof subscribers. In certain implementations, each message only need beparsed once (e.g., if multiple filters are set by multiple clients) andonly if needed based on the query instructions, as an empty filter doesnot require parsing the message.

Referring to FIG. 7A, subscriptions can include a “period” parameter,generally defined in, for example, seconds and in some embodiments canrange from 1 to 60 seconds, although other time increments and timeranges are possible. The period parameter(s) can be purely sequential(e.g., ordinal) and/or time-based (e.g., temporal) and included in theself-described data and therefore available for querying, aggregation,and the like. For example, FIG. 7A illustrates the filter processaccording to the present invention for the first three seconds with aperiod of 1 second. In the present example, the subscription starts att=0. The filter created from the query instructions is applied againstall messages received during each 1-second period (e.g., one message ata time). The results for each period are then batched and forwarded tothe subscriber. Depending on the query instructions used, the messagescan be aggregated using the aggregation functions discussed previouslybefore the message data is sent to the subscriber.

In some cases, the process defaults to sending only new, incomingmessages that meet the query instructions on to the subscriber. However,a subscriber can subscribe with history and use a filter, such that thefirst message or messages sent to the subscriber can be the historicalmessages with the filter applied. Using the period of max_age and/or a“next” parameter provides additional functionality that allows forretrieval and filtering of historical messages.

More particularly, a max_age parameter included with the queryinstructions can facilitate the retrieval of historical messages thatmeet this parameter. FIG. 7B illustrates an example of a max_ageparameter of 2 seconds (with a period of 1 second) that is provided withthe query instructions. The filter created from the query instructionsis applied to the historical messages from the channel that arrived fromt−2 through t=0 (t=0 being the time the subscription starts), and to themessages that arrived in the first period (from t=0 to t+1). Thesemessages can be sent in a single batch to the subscriber (as Group 1).The filter is applied to each message in each subsequent period (e.g.,from t+1 to t+2 as Group 2) to batch all messages that meet the queryinstructions within that period. Each batch is then forwarded on to thesubscriber.

When a subscriber subscribes with a “next” parameter to a channel with afilter, the filter can be applied to all messages from the next value upto the current message stream position for the channel, and the resultscan be sent to the subscriber in, for example, a single batch. Forexample, as illustrated in FIG. 7C, a next parameter is included withthe query instructions (with a period of 1 second). The next parameterinstructs the process to apply the filter created from the queryinstructions to each message from the “next position” up through thecurrent stream position (e.g., up to t=0) and to the messages thatarrived in the first period (from t=0 to t+1). These messages can besent in a single batch to the subscriber (as Group 1). The filter isapplied to each message in each subsequent period (e.g., from t+1 to t+2as Group 2) to batch all messages that meet the query instructionswithin that period. Each batch is then forwarded on the subscriber.

When a subscriber subscribes with a next parameter, chooses to receivehistorical messages on a channel, and includes a filter in thesubscription, the subscriber can be updated to the current messagestream position in multiple batches. FIG. 7D illustrates an example of amax_age parameter of 2 seconds (with a period of 1 second) and a nextparameter that can be combined into one set of query instructions. Thefilter created from the query instructions is applied to the historicalmessages from the channel that arrived from the end of the history tothe “next” value of the subscription (i.e., from 2 seconds before thenext value up to the next value), to the messages from the next value tothe current stream position (e.g., up to t=0), and to the messages thatarrived in the first period (from t=0 to t+1). These messages can besent in a single batch to the subscriber (as Group 1). The filter isapplied to each message in each subsequent period (e.g., from t+1 to t+2as Group 2) to batch all messages that meet the query instructionswithin that period. Each batch is then forwarded on the subscriber.Consequently, historical messages can be combined with messages thatstart at a particular period indicator and batched for transmission tothe subscriber.

The query instructions can define how one or more filters can be appliedto the incoming messages in any suitable manner. For example, theresulting filter(s) can be applied to any or all messages arriving ineach period, to any or all messages arriving across multiple periods, toany or all messages arriving in select periods, or to any or allmessages arriving on a continuous or substantially continuous basis(i.e., without the use of a period parameter such that messages are notretained before returning them to the subscriber). Such filteredmessages can be batched in any suitable manner or sent individually(e.g., one message at a time) to subscribers. In particular, thefiltered messages can be sent to the subscriber in any suitable formator syntax. For example, the following illustrates the structure ofseveral fields of a sample channel PDU that contains the message resultsfrom a filter request:

{

-   -   “action”: “channel/data”,    -   “body”: {        -   “channel”: ChannelName        -   “next”: ChannelStreamPosition        -   “messages”: [ChannelData]+ // Can be one or more messages    -   }

}

In the above channel PDU, the “channel” field can be a value (e.g.,string or other appropriate value or designation) of the channel name towhich the subscriber has subscribed. The “next” field can provide thechannel stream position of the batch of messages returned in the channelPDU. The “messages” field provides the channel data of the messagesresulting from application of the specified filter. One or more messagescan be returned in the “messages” field in such a channel PDU. It isnoted that a channel PDU can include any other suitable fields,parameters, values, or data.

FIG. 8 is a diagram of an example messaging system 800 for self-learningspatial recognition in a PubSub communication system. The system 800 mayinclude a data analyzer 830 that analyzes data frames 811 that areencoded in a message 810. The message 810, including the data frames811, may be provided through a PubSub system as described herein. Insome implementations, the data frames 811 of message 810 may includelive video frames 812 and/or a data 813 of the client device sending themessage 810. In one embodiment, message 810 may be sent from a deviceincluding a camera, directed to a geographical region, as describedherein. Additional details regarding live video frames 812 and data 813are provided with respect to FIGS. 9-11.

In one embodiment, the message 810 may pass through a network 820, suchas through a PubSub system, before arriving at a data analyzer 830. Thedata analyzer 830 may be a subscriber to a channel on which the message810 is provided or otherwise published. The data analyzer 830 mayperform one or more analysis processes to analyze the data frame 811.For example, the data analyzer 830 may apply one or more machinelearning models to the live video frames 812 to identify one or moreobjects (e.g., elements) within the live video frame 812. Data analyzer830 may apply one or more machine learning models to the data frames 811to determine their content (e.g., whether a live video frame 812 exists,whether additional data 813 exists, etc.). The data analyzer 830 may beone of a plurality of data analyzers 830 that each may analyze the dataframes 811 and/or live video frames 812 in similar or different manners.The data analyzer 830 may include one or more analysis components 831that perform different analyses. In some implementations, the analysiscomponent (e.g., 831) and/or the data analyzer 830 may provideadditional metadata that indicates whether a particular analysis hasbeen performed so that the data analyzer 830 does not repeat potentiallytime consuming or processor consuming analysis. Based on the analysisperformed by the data analyzer 830, a second message 840 may begenerated to include new or additional data, such as a processed data844. In one embodiment, processed data 844 corresponds to any elementsof the data frames 811 identified by data analyzer 830. In oneembodiment, the processed data 844 may include regions of interests, thestatus of regions of interest, maps, locations of objects, types ofobjects, etc. as described herein. The data analyzer 830 may provide thesecond message 840 over network 820. As different data analyzers 830 oranalysis components 831 perform additional analyses, the data stored inthe second message 840 may be increase or decrease. Accordingly, thedata analyzer 830 may forward the second message 840 on to subscribersof the channels at some or any point after analysis has been completed(e.g., in real time, substantially real time, or sometime later).

FIG. 9 is a first flowchart of an example method 900 for self-learningspatial recognition in a PubSub communication system. The method 900 canbe implemented using, for example, an MX node (e.g., MX node 204, MXnode 461) and a Q node (e.g., Q node 212, Q node 208) of the messagingsystem 100, for example. The method begins in block 902 by a computerprocessing device receiving a plurality of video frames from a videosource. In one embodiment, each video frame of the plurality of videoframes includes a view of a geolocation. For example, the plurality ofvideo frames may correspond to a parking lot, a parking structure, astreet, an arena, a stadium, a theater, a park, a harbor, a field, ashopping center etc. The geographical location may include any suitablelocation for self-learning spatial recognition, as described herein. Inone embodiment, the plurality of video frames from the video source is aplurality of live video frames from a live video source. Live videoframes from a live video source may be processed in real time (e.g., asthey are captured) by the PubSub system described herein. In anotherembodiment, the live video frames may be processed at a suitable, latertime.

At block 904, processing logic detecting a first object entering a firstside of a first video frame of the plurality of video frames. In oneembodiment, video frames include four sides, corresponding to top,bottom, left, and right orientations. In other embodiments, video framesmay include less or more than four sides. In one embodiment, the firstobject may be classified as an object type. For example, object typesmay include vehicles, pedestrians, etc. In another embodiment, theobject is not classified as a type, but is recognized as a movingobject.

At block 906, processing logic determines, from the plurality of videoframes, that the first object has stopped in an area of the geolocationfor at least a threshold amount of time. In one embodiment, thethreshold of time is one hour. In another embodiment, the threshold oftime is 30 minutes. In various other embodiments, any suitable thresholdof time may be used. Advantageously, by determining that the firstobject has remained in the area of the geolocation for at least athreshold of time, regions of interest may be more accurately determined(e.g., areas that are occupied for less than the threshold of time areless likely to be regions of interest, as defined herein).

At block 908, processing logic detects the first object leaving a secondside of a second video frame of the plurality of video frames. In oneembodiment, the second side of the second video frame is the same sidefrom which the first object entered the first video frame. In anotherembodiment, the second side of the second video frame is a differentside than that from which the first object entered the first videoframe. Optionally, processing logic at block 912 may determine that asize of the first object changes less than a defined threshold betweenthe first video frame and the second video frame. In one embodiment, thedefined threshold may be a ten percent change in size. In various otherembodiments, any other suitable defined threshold may be used. For alarge field of view (e.g., from wide-angle cameras), there may be adifference between object size in the center of a view and on its edge.Advantageously, by determining that the size of the first object changesless than a defined threshold between the first video frame and thesecond video frame (e.g., due to perspective), processing logic is ableto more accurately determine that the first object is of interest, andtherefore at the area occupied by the first object is a region ofinterest. For example, a bird flying through the view of the videoframes may change in size by more than the defined threshold, and maytherefore be ruled out as occupying a region of interest.

At block 910, processing logic identifies, by a computer processingdevice, the area of the geolocation as a region of interest based on thedetecting the first object leaving the second side of the video frameand further based on the determining that the first object was stoppedin the area of the geolocation for at least the threshold amount oftime. In another embodiment, if the first object was stopped in the areaof the geolocation for less than the threshold amount of time beforeleaving, the area is not identified as a region of interest. In oneembodiment, a region of interest may correspond to a parking sport, achair, a bench, a boating slip, or a position in a queue, etc., asdescribed herein. Worth noting is that processing logic may also performbackground removal according to any suitable method to assist inidentifying moving objects.

FIG. 10 is a second flowchart of an example method 1000 forself-learning spatial recognition in a PubSub communication system. Themethod 1000 can be implemented using, for example, an MX node (e.g., MXnode 204, MX node 461) and a Q node (e.g., Q node 212, Q node 208) ofthe messaging system 100, for example. The method begins in block 1002by processing logic generating, based on a region of interest, a mapcomprising the geolocation. In one embodiment, the map may includeregions of interest identified in the geolocation. The map may includealphanumeric labels for the regions of interest identified in the map.The map may further include status identifiers, to indicate whetherregions of interest are occupied or unoccupied. Alternatively or inaddition to generating a map, processing logic may generate a list ofregions of interest in the geographical location, with correspondinglabels and status identifiers.

At block 1004, processing logic determines whether a second objectoccupies the region of interest. If a second object does occupy theregion of interest, processing logic at block 1006 may mark the regionthe region of interest on the map (or list) as occupied. If a secondobject does not occupy the region of interest, processing logic may markthe region of interest as unoccupied (or leave the status identifiercorresponding to the region of interest as unoccupied, if that isalready the current designation.).

FIG. 11 is a third flowchart of an example method 1100 for self-learningspatial recognition in a PubSub communication system. The method 1100can be implemented using, for example, an MX node (e.g., MX node 204, MXnode 461) and a Q node (e.g., Q node 212, Q node 208) of the messagingsystem 100, for example. The method begins in block 1102 by processinglogic generating, based on a region of interest, a map comprising thegeolocation. Alternatively or in addition to the map, a list may begenerated, as discussed above.

At block 1104, processing logic determines whether the region ofinterest has been unoccupied for a defined threshold of time. In oneembodiment, the defined threshold of time may be 3 days. In anotherembodiment, the defined threshold of time may be one week. In variousother embodiments, any other suitable defined threshold of time may beused. If the region of interest has been unoccupied for the definedthreshold of time, at block 1106 processing logic removes the region ofinterest from the map. Advantageously, the features of method 1100 allowfor a region of interest (e.g., a parking spot) to be declassified as aregion of interest, if it is not occupied for a certain period of time(e.g., the defined threshold).

FIG. 12 is a first diagram of an example mapping for self-learningspatial recognition in a PubSub communication system. As describedherein, an object may be classified as “of interest” (e.g., car, van,truck, motorcycle, bicycle, scooter, or other suitable vehicle orpedestrian) if it entered the camera view from a side (e.g., from theleft, right, top, or bottom of the video frame), stopped for more than athreshold time, and left the camera view by crossing at one of itssides. The place where the object stopped may then be classified as aparking spot (or other type of region of interest). For example, anobject (vehicle 1202) may enter geographical region 1204 from the rightside, (e.g., 1206), park in an area (e.g., area 1208) for more than athreshold amount of time, and leave from the right side (e.g., 1206).Thereafter area 1208 may be identified as a parking spot (e.g., #1). Asshown, parking spots 2-6 may have been already identified as parkingspots, according to the operations described herein.

It is noted that the threshold of time may be chosen to differentiatebetween a vehicle (which may remain motionless for long periods of time)and, for instance, a person (which cannot). In other words, the periodof time may be chosen to allow differentiation between “interesting”objects (e.g., vehicles) and “non-interesting” objects (e.g.,non-vehicular objects) in the context of the present embodiments.Additionally or alternatively, the period of time can be chosen to allowdifferentiation between a “parked” vehicle and one that is merelymomentarily stopped or standing (e.g., a car stopped in the middle ofthe road waiting to make a turn or standing by the side of a roadwaiting to pick up a passenger). Whatever period of time is chosen, thepresent invention may take at least up to that period of time beforeinitially classifying the area as a parking spot.

Furthermore, as described above with respect to FIG. 9, during objectmovement, an object can change in size. If a change in size is more thana defined threshold (e.g., ten percent), it may be considered as noiseor caused by error in object unification (e.g., when two objects areclose enough that they could be unified by mistake). However, when thesize of the object changes less than the defined threshold, the changein size may be considered as object sizing due to perspective.Alternatively, instead of using a percentage, a suitable heuristic canbe used that can assume that a single object should remain single.

After a region of interest (e.g., a parking spot) is marked or otherwiseidentified according to the embodiments described herein, it could beoccupied by other objects for a period less than the threshold duration.In other words, once initially identified, the region of interest can bemarked as open or occupied after any suitable length of time as cars orother vehicles enter, park, and leave the parking lot.

According to the one embodiment, the boundaries of a region of interestcan be detected by, for example, extracting the difference between anoccupied region of interest and an image of the same unoccupied regionof interest. Such an exemplary embodiment can act as a type of mask orfilter that results in detecting an area that may be of arbitrary shape.For example, it is noted that shadows and other image artifacts could beincluded as part of the vehicle, which can result in an identifiedparking spot that is not necessarily rectangular in shape.

If two regions of interest have more than, for example, 50% overlap,they may be considered to be the same region of interest. In otherwords, regions of interest should be checked pairwise, such that ifregion of interest A has merged into region of interest B, then regionof interest A is no longer considered separate from region of interestB. Other values for determining overlap can be used. For instance, a 50%overlap has been provided as an illustrative example, because an objectcannot overlap with two non-overlapping objects more than 50% at thesame time. However, alternative mechanisms can be used to determineoverlap, such as with a suitable heuristic or the like.

If a region of interest has been unoccupied for a period of time thatexceeds some defined threshold (e.g., a define threshold could be abouta week, although other suitable lengths of time can also be used), itmay be removed because the region of interest could have been identifieddue to camera movement, someone using the region of interest in animproper way (e.g., parking in an emergency-vehicle-only zone), etc.

In one embodiment, various data may be generated by the embodimentsdisclosed herein. Data may include, for example: a length of time theregion of interest is occupied or unoccupied; an image of the objectthat occupied the region of interest most recently; a map of all regionsof interest in the geographical location, including labels and statusindicators (e.g., color coded); a number of current occupied andunoccupied regions of interest; etc.

As previously disclosed, the embodiments described herein are notlimited to use for parking spots in a parking lot. Rather, the presentembodiments can be used to identify open and occupied spaces in anylarge area that includes a reasonably regular and repeating pattern ofobjects. For purposes of illustration and not limitation, the presentembodiments can be used to identify parking spaces lining a road, berths(slips) in a harbor, seats in a stadium, etc.

FIG. 13 is a block diagram of an example computing device 1300 that mayperform one or more of the operations described herein. The computingdevice 1300 may be connected to other computing devices in a LAN, anintranet, an extranet, and/or the Internet. The computing device 1300may operate in the capacity of a server machine in client-server networkenvironment or in the capacity of a client in a peer-to-peer networkenvironment. The computing device 1300 may be provided by a personalcomputer (PC), a set-top box (STB), a server, a network router, switchor bridge, or any machine capable of executing a set of instructions(sequential or otherwise) that specify actions to be taken by thatmachine. Further, while only a single computing device 1300 isillustrated, the term “computing device” shall also be taken to includeany collection of computing devices that individually or jointly executea set (or multiple sets) of instructions to perform the methodsdiscussed herein.

The example computing device 1300 may include a computer processingdevice (e.g., a general purpose processor, ASIC, etc.) 1302, a mainmemory 1304, a static memory 1306 (e.g., flash memory and a data storagedevice 1308), which may communicate with each other via a bus 1310. Thecomputer processing device 1302 may be provided by one or moregeneral-purpose processing devices such as a microprocessor, centralprocessing unit, or the like. In an illustrative example, computerprocessing device 1302 may comprise a complex instruction set computing(CISC) microprocessor, reduced instruction set computing (RISC)microprocessor, very long instruction word (VLIW) microprocessor, or aprocessor implementing other instruction sets or processors implementinga combination of instruction sets. The computer processing device 1302may also comprise one or more special-purpose processing devices such asan application specific integrated circuit (ASIC), a field programmablegate array (FPGA), a digital signal processor (DSP), network processor,or the like. The computer processing device 1302 may be configured toexecute the operations described herein, in accordance with one or moreaspects of the present disclosure, for performing the operations andsteps discussed herein.

The computing device 1300 may further include a network interface device1312, which may communicate with a network 1314. The data storage device1308 may include a machine-readable storage medium 1316 on which may bestored one or more sets of instructions, e.g., instructions for carryingout the operations described herein, in accordance with one or moreaspects of the present disclosure. Instructions implementing module 1318may also reside, completely or at least partially, within main memory1304 and/or within computer processing device 1302 during executionthereof by the computing device 1300, main memory 1304 and computerprocessing device 1302 also constituting computer-readable media. Theinstructions may further be transmitted or received over the network1314 via the network interface device 1312.

While machine-readable storage medium 1316 is shown in an illustrativeexample to be a single medium, the term “computer-readable storagemedium” should be taken to include a single medium or multiple media(e.g., a centralized or distributed database and/or associated cachesand servers) that store the one or more sets of instructions. The term“computer-readable storage medium” shall also be taken to include anymedium that is capable of storing, encoding or carrying a set ofinstructions for execution by the machine and that cause the machine toperform the methods described herein. The term “computer-readablestorage medium” shall accordingly be taken to include, but not belimited to, solid-state memories, optical media and magnetic media.

Embodiments of the subject matter and the operations described in thisspecification can be implemented in digital electronic circuitry, or incomputer software, firmware, or hardware, including the structuresdisclosed in this specification and their structural equivalents, or incombinations of one or more of them. Embodiments of the subject matterdescribed in this specification can be implemented as one or morecomputer programs, i.e., one or more modules of computer programinstructions, encoded on computer storage medium for execution by, or tocontrol the operation of, data processing apparatus. Alternatively or inaddition, the program instructions can be encoded on anartificially-generated propagated signal, e.g., a machine-generatedelectrical, optical, or electromagnetic signal that is generated toencode information for transmission to suitable receiver apparatus forexecution by a data processing apparatus. A computer storage medium canbe, or be included in, a computer-readable storage device, acomputer-readable storage substrate, a random or serial access memoryarray or device, or a combination of one or more of them. Moreover,while a computer storage medium is not a propagated signal, a computerstorage medium can be a source or destination of computer programinstructions encoded in an artificially-generated propagated signal. Thecomputer storage medium can also be, or be included in, one or moreseparate physical components or media (e.g., multiple CDs, disks, orother storage devices).

The operations described in this specification can be implemented asoperations performed by a data processing apparatus on data stored onone or more computer-readable storage devices or received from othersources.

The term “computer processing device” encompasses all kinds ofapparatus, devices, and machines for processing data, including by wayof example a programmable processor, a computer, a system on a chip, ormultiple ones, or combinations, of the foregoing. Although referred toas a computer processing device, use of the term also encompassesembodiments that include one or more computer processing devices. Thecomputer processing device can include special purpose logic circuitry,e.g., an FPGA (field programmable gate array) or an ASIC(application-specific integrated circuit). The computer processingdevice can also include, in addition to hardware, code that creates anexecution environment for the computer program in question, e.g., codethat constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, a cross-platform runtimeenvironment, a virtual machine, or a combination of one or more of them.The computer processing device and execution environment can realizevarious different computing model infrastructures, such as web services,distributed computing and grid computing infrastructures.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, declarative,procedural, or functional languages, and it can be deployed in any form,including as a stand-alone program or as a module, component,subroutine, object, or other unit suitable for use in a computingenvironment. A computer program may, but need not, correspond to a filein a file system. A program can be stored in a portion of a file thatholds other programs or data (e.g., one or more scripts stored in amarkup language resource), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub-programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform actions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application-specific integrated circuit).

Processing devices suitable for the execution of a computer programinclude, by way of example, both general and special purposemicroprocessors, and any one or more processors of any kind of digitalcomputer. Generally, a processing device will receive instructions anddata from a read-only memory or a random access memory or both. Theessential elements of a computer are a processor for performing actionsin accordance with instructions and one or more memory devices forstoring instructions and data. Generally, a computer will also include,or be operatively coupled to receive data from or transfer data to, orboth, one or more mass storage devices for storing data, e.g., magneticdisks, magneto-optical disks, optical disks, or solid state drives.However, a computer need not have such devices.

Moreover, a computer can be embedded in another device, e.g., a smartphone, a mobile audio or video player, a game console, a GlobalPositioning System (GPS) receiver, or a portable storage device (e.g., auniversal serial bus (USB) flash drive), to name just a few. Devicessuitable for storing computer program instructions and data include allforms of non-volatile memory, media and memory devices, including, byway of example, semiconductor memory devices, e.g., EPROM, EEPROM, andflash memory devices; magnetic disks, e.g., internal hard disks orremovable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.The processing device and the memory can be supplemented by, orincorporated in, special purpose logic circuitry.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a computerhaving a display device, e.g., a CRT (cathode ray tube) or LCD (liquidcrystal display) monitor, for displaying information to the user and akeyboard and a pointing device, e.g., a mouse, a trackball, a touchpad,or a stylus, by which the user can provide input to the computer. Otherkinds of devices can be used to provide for interaction with a user aswell; for example, feedback provided to the user can be any form ofsensory feedback, e.g., visual feedback, auditory feedback, or tactilefeedback; and input from the user can be received in any form, includingacoustic, speech, or tactile input. In addition, a computer can interactwith a user by sending resources to and receiving resources from adevice that is used by the user; for example, by sending web pages to aweb browser on a user's client device in response to requests receivedfrom the web browser.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back-end component,e.g., as a data server, or that includes a middleware component, e.g.,an application server, or that includes a front-end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back-end, middleware, or front-end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include a local area network (“LAN”) and a widearea network (“WAN”), an inter-network (e.g., the Internet), andpeer-to-peer networks (e.g., ad hoc peer-to-peer networks).

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other. In someembodiments, a server transmits data (e.g., an HTML page) to a clientdevice (e.g., for purposes of displaying data to and receiving userinput from a user interacting with the client device). Data generated atthe client device (e.g., a result of the user interaction) can bereceived from the client device at the server.

A system of one or more computers can be configured to performparticular operations or actions by virtue of having software, firmware,hardware, or a combination of them installed on the system that inoperation causes or cause the system to perform the actions. One or morecomputer programs can be configured to perform particular operations oractions by virtue of including instructions that, when executed by dataprocessing apparatus, cause the apparatus to perform the actions.

While this specification contains many specific implementation details,these should not be construed as limitations on the scope of anyinventions or of what may be claimed, but rather as descriptions offeatures specific to particular embodiments of particular inventions.Certain features that are described in this specification in the contextof separate embodiments can also be implemented in combination in asingle embodiment. Conversely, various features that are described inthe context of a single embodiment can also be implemented in multipleembodiments separately or in any suitable subcombination. Moreover,although features may be described above as acting in certaincombinations and even initially claimed as such, one or more featuresfrom a claimed combination can in some cases be excised from thecombination, and the claimed combination may be directed to asubcombination or variation of a subcombination.

Similarly, while operations are depicted in the drawings in a particularorder, this should not be understood as requiring that such operationsbe performed in the particular order shown or in sequential order, orthat all illustrated operations be performed, to achieve desirableresults. In certain circumstances, multitasking and parallel processingmay be advantageous. Moreover, the separation of various systemcomponents in the embodiments described above should not be understoodas requiring such separation in all embodiments, and it should beunderstood that the described program components and systems cangenerally be integrated together in a single software product orpackaged into multiple software products.

Thus, particular embodiments of the subject matter have been described.Other embodiments are within the scope of the following claims. In somecases, the actions recited in the claims can be performed in a differentorder and still achieve desirable results. In addition, the processesdepicted in the accompanying figures do not necessarily require theparticular order shown, or sequential order, to achieve desirableresults. In certain implementations, multitasking and parallelprocessing may be advantageous.

What is claimed is:
 1. A method, comprising: receiving a plurality ofvideo frames from a video source, wherein each video frame of theplurality of video frames comprises a view of a geolocation; detecting afirst object entering a first side of a first video frame of theplurality of video frames; determining, from the plurality of videoframes, that the first object has stopped in an area of the geolocationfor at least a threshold amount of time; detecting the first objectleaving a second side of a second video frame of the plurality of videoframes; and identifying, by a computer processing device, the area ofthe geolocation as a region of interest based on the detecting the firstobject leaving.
 2. The method of claim 1, wherein the plurality of videoframes from the video source is a plurality of live video frames from alive video source.
 3. The method of claim 1, further comprisingdetermining that a size of the first object changes less than a definedthreshold between the first video frame and the second video frame. 4.The method of claim 1, further comprising generating, based on theregion of interest, a map comprising the geolocation.
 5. The method ofclaim 4, further comprising: determining that a second object occupiesthe region of interest; and marking the region of interest on the map asoccupied.
 6. The method of claim 4, further comprising: determining thatthe region of interest has not been occupied for a defined threshold oftime; and removing the region of interest from the map.
 7. The method ofclaim 1, wherein the region of interest corresponds to a parking spot.8. The method of claim 7, wherein the first object corresponds to avehicle.
 9. The method of claim 1, wherein the region of interestcorresponds to at least one of a chair, a bench, or a position in aqueue, and wherein the geolocation corresponds to at least one of anarena, a stadium, a theater, a field, or a shopping center.
 10. Themethod of claim 9, wherein the first object corresponds to at least oneof a vehicle or a pedestrian.
 11. A system, comprising a computerprocessing device programmed to perform operations to: receive aplurality of video frames from a video source, wherein each video frameof the plurality of video frames comprises a view of a geolocation;detect a first object entering a first side of a first video frame ofthe plurality of video frames; determine, from the plurality of videoframes, that the first object has stopped in an area of the geolocationfor at least a threshold amount of time; detect the first object leavinga second side of a second video frame of the plurality of video frames;and identify the area of the geolocation as a region of interest basedon the detecting the first object leaving.
 12. The system of claim 11,wherein the plurality of video frames from the video source is aplurality of live video frames from a live video source.
 13. The systemof claim 11, the computer processing device further to determine that asize of the first object changes less than a defined threshold betweenthe first video frame and the second video frame.
 14. The system ofclaim 11, the computer processing device further to generate, based onthe region of interest, a map comprising the geolocation.
 15. The systemof claim 14, the computer processing device further to: determine that asecond object occupies the region of interest; and mark the region ofinterest on the map as occupied.
 16. The system of claim 14, thecomputer processing device further to: determine that the region ofinterest has not been occupied for a defined threshold of time; andremove the region of interest from the map.
 17. The system of claim 11,wherein the region of interest corresponds to a parking spot, andwherein the first object corresponds to a vehicle.
 18. The system ofclaim 11, wherein the region of interest corresponds to at least one ofa chair, a bench, or a position in a queue, and wherein the geolocationcorresponds to at least one of an arena, a stadium, a theater, a field,or a shopping center, and wherein the first object corresponds to atleast one of a vehicle or a pedestrian.
 19. A non-transitorycomputer-readable medium having instructions stored thereon that, whenexecuted by a computer processing device, cause the computer processingdevice to: receive a plurality of video frames from a video source,wherein each video frame of the plurality of video frames comprises aview of a geolocation; detect a first object entering a first side of afirst video frame of the plurality of video frames; determine, from theplurality of video frames, that the first object has stopped in an areaof the geolocation for at least a threshold amount of time; detect thefirst object leaving a second side of a second video frame of theplurality of video frames; and identify, by the computer processingdevice, the area of the geolocation as a region of interest based on thedetecting the first object leaving.
 20. The non-transitorycomputer-readable medium of claim 19, wherein the plurality of videoframes from the video source is a plurality of live video frames from alive video source.